metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_beit_base_sgd_00001_fold2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.40099833610648916
smids_5x_beit_base_sgd_00001_fold2
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.1209
- Accuracy: 0.4010
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1533 | 1.0 | 375 | 1.3089 | 0.3344 |
| 1.2124 | 2.0 | 750 | 1.2999 | 0.3344 |
| 1.1985 | 3.0 | 1125 | 1.2914 | 0.3428 |
| 1.1579 | 4.0 | 1500 | 1.2833 | 0.3461 |
| 1.1291 | 5.0 | 1875 | 1.2755 | 0.3461 |
| 1.194 | 6.0 | 2250 | 1.2681 | 0.3478 |
| 1.2016 | 7.0 | 2625 | 1.2608 | 0.3494 |
| 1.1347 | 8.0 | 3000 | 1.2537 | 0.3527 |
| 1.1472 | 9.0 | 3375 | 1.2468 | 0.3577 |
| 1.15 | 10.0 | 3750 | 1.2403 | 0.3611 |
| 1.1134 | 11.0 | 4125 | 1.2339 | 0.3661 |
| 1.1681 | 12.0 | 4500 | 1.2277 | 0.3694 |
| 1.1002 | 13.0 | 4875 | 1.2218 | 0.3677 |
| 1.1221 | 14.0 | 5250 | 1.2161 | 0.3677 |
| 1.0969 | 15.0 | 5625 | 1.2104 | 0.3694 |
| 1.1378 | 16.0 | 6000 | 1.2051 | 0.3694 |
| 1.0509 | 17.0 | 6375 | 1.1999 | 0.3727 |
| 1.0539 | 18.0 | 6750 | 1.1948 | 0.3727 |
| 1.1469 | 19.0 | 7125 | 1.1900 | 0.3760 |
| 1.0806 | 20.0 | 7500 | 1.1853 | 0.3760 |
| 1.1095 | 21.0 | 7875 | 1.1807 | 0.3760 |
| 1.0474 | 22.0 | 8250 | 1.1764 | 0.3760 |
| 1.0756 | 23.0 | 8625 | 1.1722 | 0.3810 |
| 1.1044 | 24.0 | 9000 | 1.1682 | 0.3794 |
| 1.1189 | 25.0 | 9375 | 1.1645 | 0.3844 |
| 1.0607 | 26.0 | 9750 | 1.1609 | 0.3844 |
| 1.1097 | 27.0 | 10125 | 1.1574 | 0.3844 |
| 1.0713 | 28.0 | 10500 | 1.1541 | 0.3860 |
| 1.0338 | 29.0 | 10875 | 1.1510 | 0.3877 |
| 1.0753 | 30.0 | 11250 | 1.1479 | 0.3910 |
| 1.0493 | 31.0 | 11625 | 1.1452 | 0.3910 |
| 1.0423 | 32.0 | 12000 | 1.1425 | 0.3910 |
| 1.0585 | 33.0 | 12375 | 1.1400 | 0.3943 |
| 1.0104 | 34.0 | 12750 | 1.1377 | 0.3960 |
| 1.0421 | 35.0 | 13125 | 1.1356 | 0.3960 |
| 1.0328 | 36.0 | 13500 | 1.1336 | 0.3977 |
| 1.0499 | 37.0 | 13875 | 1.1317 | 0.3993 |
| 1.0006 | 38.0 | 14250 | 1.1300 | 0.4010 |
| 1.0528 | 39.0 | 14625 | 1.1285 | 0.4010 |
| 1.0416 | 40.0 | 15000 | 1.1271 | 0.4010 |
| 1.0633 | 41.0 | 15375 | 1.1258 | 0.4010 |
| 1.0643 | 42.0 | 15750 | 1.1247 | 0.4027 |
| 1.0051 | 43.0 | 16125 | 1.1238 | 0.4027 |
| 1.0289 | 44.0 | 16500 | 1.1230 | 0.4027 |
| 0.9766 | 45.0 | 16875 | 1.1223 | 0.4010 |
| 1.0401 | 46.0 | 17250 | 1.1218 | 0.4010 |
| 1.0257 | 47.0 | 17625 | 1.1214 | 0.4010 |
| 1.0309 | 48.0 | 18000 | 1.1211 | 0.4010 |
| 1.0074 | 49.0 | 18375 | 1.1210 | 0.4010 |
| 1.0327 | 50.0 | 18750 | 1.1209 | 0.4010 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2